Nowadays everything is apparently in the cloud. However the cloud comes in many different sizes and shapes. In my case primarily in the form of dropbox. However there are always downsides of “out sourcing” your data to an undefined cloud. Some popular alternatives include BitTorrent Sync (not open source and your data is still touched by a third party), ownCloud (an open source dropbox clone, however the performance on a Raspberry Pi is not very smooth) and since December 2013 Syncthing. The last one is a kind of open source implementation of BitTorrent Sync, so in contrast to Dropbox your data is distributed over your own computers and not at a distant server. In my setup I use a headless Raspberry Pi that is tucked a way in a cupboard as a node in the network, so this client is always online. Continue reading
Tag Archives: data
Last week I attended the Visualizing Biological Data (VizBi) conference in Heidelberg. According to the website the mission of the conference is to “ bring together scientists, illustrators, and designers actively using or developing computational visualization to study a diverse range of biological data.”. I can only say the organisers more than succeeded in this mission, it was indeed a very interdisciplinary, creative and interactive crowd. The first keynote of VizBi ’14 was presented by Jeffrey Heer from the University of Washington, since the papers he referred to are mostly published in non-PubMed journals I tried to collect links to the pdfs here. Update: Added two more references supplied by Heer.
Currently I’m participating in the Quantified Self summer school at the CIID (Copenhagen Institute for Interaction Design). The focus lies on the visualisation of complex data sets, currently a hot topic in science. As workhorse the Java based environment Processing is used, which is widely known in the visualization community. (For some vivid examples check openprocessing.org).
To get a better grasp of Java in general and processing in particular I wrote a small package that visualizes all the places you have visited with the corresponding color mood (=the most prominent color in the pictures you took).